Table 5 Computational complexity analysis of different feature selection techniques.
Technique | Type | Computational Complexity | Remarks |
|---|---|---|---|
Chi-Square | Filter | \(O(n\times m)\) | Fast for continuous features |
ANOVA | Filter | \(O(n\times m)\) | Fast for continuous features |
LASSO | Embedded | \(O(k\times n\times m)\)/iteration | Requires iterative convergence |
XGBoost | Embedded | \(O(k1\times m\times \text{log}(n))\) per tree | Good accuracy rates |
EEFOA | Wrapper | \(O(p\times k\times c)\) | Slow in speed, but most effective |
